Authors :
Dr. K. V. Vijila; Dr. Priya Ramani; Dr. Mohamed Yasin; Dr. Nithish Kumar; Dr. Mohammed Alia Ruqsana
Volume/Issue :
Volume 9 - 2024, Issue 12 - December
Google Scholar :
https://tinyurl.com/34mpb83d
Scribd :
https://tinyurl.com/yc3tyxmn
DOI :
https://doi.org/ 10.5281/zenodo.14558001
Abstract :
Oral medicine plays a pivotal role in
diagnostic decision-making and the field has witnessed
significant advancements over time, revolutionizing the
way oral diseases are diagnosed and managed. Recent
advancements in diagnostic oral medicine offer
promising solutions for early detection and accurate
diagnosis. These innovations include the use of salivary
biomarkers, advanced imaging technologies, and
artificial intelligence (AI). Early detection is crucial for
improving patient outcomes. Saliva-based biomarkers,
such as miRNAs and proteins, provide a non-invasive
method for early detection. Imaging techniques like auto
fluorescence imaging, Raman spectroscopy, and optical
coherence tomography enhances the visualization of
abnormal tissues. AI-powered tools, particularly deep
learning algorithms, can analyze images and data to
improve diagnostic accuracy. By combining these
technologies, we can achieve earlier detection, more
accurate diagnosis, and personalized treatment plans for
oral cancer patients.
Keywords :
Oral cancer, Biomarkers, Artificial Intelligence, Nanotechnology, Chemiluminescence, Brush Biopsy.
References :
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Oral medicine plays a pivotal role in
diagnostic decision-making and the field has witnessed
significant advancements over time, revolutionizing the
way oral diseases are diagnosed and managed. Recent
advancements in diagnostic oral medicine offer
promising solutions for early detection and accurate
diagnosis. These innovations include the use of salivary
biomarkers, advanced imaging technologies, and
artificial intelligence (AI). Early detection is crucial for
improving patient outcomes. Saliva-based biomarkers,
such as miRNAs and proteins, provide a non-invasive
method for early detection. Imaging techniques like auto
fluorescence imaging, Raman spectroscopy, and optical
coherence tomography enhances the visualization of
abnormal tissues. AI-powered tools, particularly deep
learning algorithms, can analyze images and data to
improve diagnostic accuracy. By combining these
technologies, we can achieve earlier detection, more
accurate diagnosis, and personalized treatment plans for
oral cancer patients.
Keywords :
Oral cancer, Biomarkers, Artificial Intelligence, Nanotechnology, Chemiluminescence, Brush Biopsy.